Lead Reliability & Availability Engineer
Greenville, NC - USA
Job Summary
Your mission is to serve as the architect of turbine reliability modeling applying mechanical and systems engineering principles to massive fleet datasets. You will transform raw performance data into actionable reliability models and high-fidelity availability forecasts that directly inform the design of more durable hardware optimize service contracts and set customer performance expectations.
Roles and Responsibilities
Failure Analysis:Ingest and analyze performance data to identify the physical drivers of turbine unavailability. You must be able to distinguish between technical component failures turbine/component design architecture and manufacturing differences.
Probabilistic Modeling:Develop component-level reliability models to predict the life cycle of critical turbine systems (e.g. drivetrains bearings blades) utilizing statistical analysis methods.
Design Verification:Partner with Design Engineering teams to set reliability targets for new products. Verify that replacement parts meet or exceed the performance of the original components.
Infrastructure Management:Own the data pipeline for statistical analysis methods. Manage data governance execute data pulls and ensure high-fidelity reporting for critical asset dashboards (e.g. Main Bearing performance).
Inventory Optimization:Use data-driven projections to forecast spare part demand balancing inventory levels with the need for immediate turbine return-to-service.
Technical Forecasting:Build statistical forecasts for fleet-wide availability to support Long-Term Service Agreements (LTSA) and financial risk management.
Hardware Simulation:Model the expected performance lift of proposed fleet retrofits or design changes before capital is deployed.
Required Qualifications
- Bachelors degree in Mechanical Engineering Electrical Engineering or a closely related engineering field (e.g. Systems Engineering).
- At least 3 years of professional or internship experience in an industrial setting preferably in wind energy power generation or heavy-duty machinery.
- At least 1 years professional or internship experience in probability and statistics as applied to physical engineering systems.
Desired Characteristics
- Candidates with a pure Data Science or Statistics degree must demonstrate substantial industrial/mechanical engineering experience.
Engineering Application of Data:Proven ability to apply software (Python JMP/JSL R) and query languages (SQL Databricks Redshift) to solve physical engineering problems.We are looking for engineers who use code as an enabler to improve hardware rather than generalist data scientists focusing on information architecture.
Domain Knowledge:Demonstrated understanding of physical failure modes asset lifecycle management and mechanical nuances of rotating machinery.
Communication:Ability to bridge the gap between complex engineering data and high-level stakeholders distilling technical findings into clear actionable conclusions for the business.
Program Capability: Exposure to programmatic tool usage such as Gantt charts and the demonstrated ability to self-plan and execute work scope with limited oversight
GE Vernova offers a great work environment professional development challenging careers and competitive compensation. GE Vernova is anEqual Opportunity Employer. Employment decisions are made without regard to race color religion national or ethnic origin sex sexual orientation gender identity or expression age disability protected veteran status or other characteristics protected by law.
GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
Relocation Assistance Provided: Yes
Required Experience:
IC
About Company
GE Vernova's Asset Performance Management software can help you increase asset reliability, minimize costs and reduce operational risks. View a demo today.